Excess economic burden of multimorbidity: a population-based study in Italy.

t In Italy the increasing incidence of chronic disease and multimorbidity are major challenges for health systems. When a patient suffers from more than one chronic condition, the conditions can interact causing a significant increase in patients’ care needs. Using healthcare administrative databases of Tuscany region to identify cohorts of chronic prevalent patients and their total direct healthcare expenses, in this paper we aim to study the economic burden of multiple chronic conditions and calculate the excess cost when comorbidities occur in order to assess how combinations of chronic conditions in adults affect total direct health expenditure

Inference for big data assisted by small area methods: an application to OBEC (on-line based enterprise characteristics)

Nowadays, the availability of a huge amount of data produced by a wide range of new technologies, so-called big data, is increasing. However, data obtain- able from big data sources are often the result of a non-probability sampling process and adjusting for the selection bias is an important practical problem. In this paper, we propose a novel method of reducing the selection bias associated with the big data source in the context of Small Area Estimation (SAE). Our approach is based on data integration and the combination of a big data sample and a probability sam- ple. An application on OBEC (on-line based enterprise characteristics) combining Istat sampling survey and web scraping data has been proposed

Intraoperative use of tranexamic acid to reduce transfusion rate in patients undergoing radical retropubic prostatectomy: double blind, randomised, placebo controlled trial

Objectives To determine the efficacy of intraoperative treatment with low dose tranexamic acid in reducing the rate of perioperative transfusions in patients undergoing radical retropubic prostatectomy

Membrane targeted Azobenzene drives optical modulation of bacterial membrane potential

Recent studies have shown that bacterial membrane potential is dynamic and plays signaling roles. Yet, little is still known about the mechanisms of membrane potential dynamics regulation—owing to a scarcity of appropriate research tools. Optical modulation of bacterial membrane potential could fill this gap and provide a new approach for studying and controlling bacterial physiology and electrical signaling. Here, the authors show that a membrane-targeted azobenzene (Ziapin2) can be used to photo-modulate the membrane potential in cells of the Gram-positive bacterium Bacillus subtilis. It is found that upon exposure to blue–green light (λ = 470 nm), isomerization of Ziapin2 in the bacteria membrane induces hyperpolarization of the potential. To investigate the origin of this phenomenon, ion-channel-deletion strains and ion channel blockers are examined. The authors found that in presence of the chloride channel blocker idanyloxyacetic acid-94 (IAA-94) or in absence of KtrAB potassium transporter, the hyperpolarization response is attenuated. These results reveal that the Ziapin2 isomerization can induce ion channel opening in the bacterial membrane and suggest that Ziapin2 can be used for studying and controlling bacterial electrical signaling. This new optical tool could contribute to better understand various microbial phenomena, such as biofilm electric signaling and antimicrobial resistance

Measuring Latent Variables is space and/or time: A Gender Statistics exercise

This paper concerns a Multivariate Latent Markov Model recently introduced in the literature for estimating latent traits in social sciences. Based on its ability of simultaneously dealing with longitudinal and spacial data, the model is proposed when the latent response variable is expected to have a time and space dynamic of its own, as an innovative alternative to popular methodologies such as the construction of composite indicators and structural equation modeling. The potentials of the proposed model and the added value with respect to the traditional weighted composition methodology, are illustrated via an empirical Gender Statistics exercise, focused on gender gap as the latent status to be measured and based on supranational official statistics for 30 European countries in the period 2010-2015

Measuring Latent Variables in Space and/or Time: A Gender Statistics exercise

This paper concerns a Multivariate Latent Markov Model recently introduced in the literature for estimating latent traits in social sciences. Based on its ability of simultaneously dealing with longitudinal and spacial data, the model is proposed when the latent response variable is expected to have a time and space dynamic of its own, as an innovative alternative to popular methodologies such as the construction of composite indicators and structural equation modeling. The potentials of the proposed model and the added value with respect to the traditional weighted composition methodology, are illustrated via an empirical Gender Statistics exercise, focused on gender gap as the latent status to be measured and based on supranational o cial statistics for 30 European countries in the period 2010–2015

Dietary Intake of Meat Cooking-Related Mutagens (HCAs) and Risk of Colorectal Adenoma and Cancer: A Systematic Review and Meta-Analysis

Much evidence suggests that the positive association between meat intake and colorectal adenoma (CRA) and cancer (CRC) risk is mediated by mutagenic compounds generated during cooking at high temperature. A number of epidemiological studies have estimated the effect of meat-related mutagens intake on CRC/CRA risk with contradictory and sometimes inconsistent results. A literature search was carried out (PubMed, Web of Science and Scopus) to identify articles reporting the relationship between the intake of meat-related mutagens (2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP), 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline (MeIQx), 2-amino-3,4,8-trimethylimidazo[4,5-f] quinoxaline: DiMeIQx, benzo(a) pyrene (B(a)P) and “meat derived mutagenic activity” (MDM)) and CRC/CRA risk. A random-effect model was used to calculate the risk association. Thirty-nine studies were included in the systematic review and meta-analysis. Polled CRA risk (15229 cases) was significantly increased by intake of PhIP (OR = 1.20; 95% CI: 1.13,1.28; p < 0.001), MeIQx (OR = 1.14; 95% CI: 1.05,1.23; p = 0.001), DiMeIQx (OR = 1.13; 95% CI: 1.05,1.21; p = 0.001), B(a)P (OR = 1.10; 95% CI: 1.02,1.19; p = 0.017) and MDM (OR = 1.17; 95% CI: 1.07,1.28; p = 0.001). A linear and curvilinear trend was observed in dose–response meta-analysis between CRA risk in association with PhIP, MDM, and MeIQx. CRC risk (21,344 cases) was increased by uptake of MeIQx (OR = 1.14; 95% CI: 1.04,1.25; p = 0.004), DiMeIQx (OR = 1.12; 95% CI: 1.02,1.22; p = 0.014) and MDM (OR = 1.12; 95% CI: 1.06,1.19; p < 0.001). No publication bias could be detected, whereas heterogeneity was in some cases rather high. Mutagenic compounds formed during cooking of meat at high temperature may be responsible of its carcinogenicity